Staff Machine Learning Engineer
WFA Digital Insight
As the demand for AI and machine learning specialists continues to surge, with a 25% growth in remote job postings in 2025, Twilio's Staff Machine Learning Engineer role stands out. With a strong focus on remote-first work and a culture of connection, Twilio offers a unique opportunity for professionals to make a global impact. Candidates should be prepared to leverage their skills in machine learning, data engineering, and cloud computing to drive innovation in the communications industry. With the right skills and experience, this role can be a catalyst for career growth and development.
Job Description
About the Role
The Staff Machine Learning Engineer role at Twilio is a critical component of the company's Trust Intelligence Platform team. As a key member of this team, you will be responsible for designing, building, and operating the cloud-native data and ML infrastructure that powers every customer interaction. This is a hands-on, builder-focused role that offers clear technical ownership, mentoring, and growth opportunities.In this role, you will be working closely with product, data science, and security teams to ship resilient, compliant services. You will be responsible for architecting, implementing, and maintaining scalable data pipelines and feature stores for batch and real-time workloads. Your expertise in machine learning, data engineering, and cloud computing will be essential in driving the development of Twilio's Trust Intelligence Platform.
The Trust Intelligence Platform team is a rapidly growing team that is passionate about using AI and machine learning to drive innovation in the communications industry. As a Staff Machine Learning Engineer, you will be part of a vibrant team with diverse experiences, making a global impact each day.
What You Will Do
- Architect, implement, and maintain scalable data pipelines and feature stores for batch and real-time workloads
- Build reproducible ML training, evaluation, and inference workflows using modern orchestration and MLOps tooling
- Integrate event streams from Twilio products into unified, analytics-ready datasets
- Monitor, test, and improve data quality, model performance, latency, and cost
- Partner with product, data science, and security teams to ship resilient, compliant services
- Automate deployment with CI/CD, infrastructure-as-code, and container orchestration best practices
- Produce clear documentation, dashboards, and runbooks; share knowledge through code reviews and brown-bag sessions
- Embrace Twilio's 'We are Builders' values by taking ownership of problems and driving them to completion
- Collaborate with cross-functional teams to identify and prioritize project requirements
- Develop and maintain technical roadmaps and architecture diagrams
What We Are Looking For
- B.S. in Computer Science, Data Engineering, Electrical Engineering, Mathematics, or related field—or equivalent practical experience
- 4-8 years building and operating data or ML systems in production
- Proficient in Python and SQL; comfortable with software engineering fundamentals (testing, version control, code reviews)
- Hands-on experience with ETL/ELT orchestration tools (e.g., Airflow, Dagster) and cloud data warehouses (Snowflake, BigQuery, or Redshift)
- Familiarity with ML lifecycle tooling such as MLflow, SageMaker, Vertex AI, or similar
- Working knowledge of Docker and Kubernetes
- Strong understanding of machine learning concepts, including supervised and unsupervised learning
- Experience with agile development methodologies and version control systems
Nice to Have
- Experience with natural language processing or computer vision
- Knowledge of cloud security and compliance frameworks
- Familiarity with Twilio's products and services
- Experience with DevOps tools such as Jenkins, GitLab, or CircleCI
- Certification in machine learning or data engineering
Benefits and Perks
- Competitive salary and benefits package
- Flexible working hours and remote work options
- Professional development opportunities, including training and conference attendance
- Access to cutting-edge technologies and tools
- Collaborative and dynamic work environment
- Recognition and reward programs for outstanding performance
- Comprehensive health insurance and wellness programs
- Generous paid time off and holiday policy
How to Stand Out
- Tip: Showcase your experience with machine learning and data engineering by highlighting specific projects and achievements in your resume and cover letter.
- To stand out, emphasize your ability to work collaboratively with cross-functional teams and your experience with agile development methodologies.
- Be prepared to discuss your understanding of machine learning concepts, including supervised and unsupervised learning, and how you have applied them in previous roles.
- Demonstrate your proficiency in Python and SQL, as well as your experience with ETL/ELT orchestration tools and cloud data warehouses.
- Research Twilio's products and services to understand how your skills and experience align with the company's goals and mission.
- Be prepared to discuss your experience with DevOps tools and your understanding of cloud security and compliance frameworks.
- Show a willingness to learn and adapt to new technologies and tools, and be open to feedback and continuous improvement.
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